ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices

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Pubblicato in:Behavior Research Methods (Online) vol. 43, no. 1 (Mar 2011), p. 56-65
Autore principale: Wilderjans, Tom F
Altri autori: Ceulemans, Eva, Van Mechelen, Iven, Depril, Dirk
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Springer Nature B.V.
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100 1 |a Wilderjans, Tom F 
245 1 |a ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices 
260 |b Springer Nature B.V.  |c Mar 2011 
513 |a Feature Journal Article 
520 3 |a In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering modelmay be appropriate. In this model: (1) each objectmay belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix. [PUBLICATION ABSTRACT]   In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix. 
650 2 2 |a Algorithms 
650 2 2 |a Automatic Data Processing 
650 1 2 |a Behavioral Sciences  |x statistics & numerical data 
650 1 2 |a Cluster Analysis 
650 2 2 |a Data Interpretation, Statistical 
650 2 2 |a Humans 
650 2 2 |a Internet 
650 1 2 |a Models, Statistical 
650 1 2 |a Software 
650 1 2 |a User-Computer Interface 
653 |a Studies 
653 |a User interface 
653 |a Research 
653 |a Methods 
653 |a Psychology 
653 |a Matrices 
653 |a Data 
653 |a Additives 
653 |a Clustering 
653 |a Profiles 
700 1 |a Ceulemans, Eva 
700 1 |a Van Mechelen, Iven 
700 1 |a Depril, Dirk 
773 0 |t Behavior Research Methods (Online)  |g vol. 43, no. 1 (Mar 2011), p. 56-65 
786 0 |d ProQuest  |t Health & Medical Collection 
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